
In solving Boolean satisfiability problems, the sIM is able to beat competition-winning SAT solvers (2020, 2017) in run-time by up to 4-700x to reach 95% accuracy.

In probabilistic sampling, the sIM delivers a measured 5-18x speedup over the optimized TPU and GPU implementations (Table REF ). Against a standard CPU implementation, we measure up to 6-orders of magnitude speedup.

In integer factorization, the sIM can reliably find the absolute ground state for semiprimes up to 32-bits, far larger than what has been reported for D-Wave's quantum annealers or similar probabilistic solvers [1]}, [2]}, [3]}, [4]}, [5]}, [6]} (Table REF ). Robust factorization up to 32-bit numbers seem to be the largest by far among these alternatives.

